Industrial process control and automation systems are routinely used to automate large and complex industrial processes. Maintaining the equipment in industrial processes can be financially burdensome due to things like the costs of equipment replacements and lost operating times when equipment fails. Predictive algorithms can be used to predict whether a piece of equipment is experiencing a problem or about to fail, allowing maintenance to be scheduled for that piece of equipment. However, when designing an algorithm to predict whether a piece of equipment requires maintenance, the algorithm's developer is often faced with a dilemma. Algorithms typically use a threshold value to determine whether maintenance for a piece of equipment is needed. If the threshold value is too low, the algorithm results in too many service calls for equipment that is functional. If the threshold value is too high, the algorithm may not schedule adequate maintenance for faulty equipment.